From the article: "The goal of higher professional education is to enable students to develop into reflective practitioners, having both a firm theoretical knowledge base as well as appropriate, professional attitudes and skills. Learning at the workplace is crucial in professional education, because it allows students to learn to act competently in complex contexts and unpredictable situations. Reflection on learning during an internship is hard to interweave with the working process, which may easily result in students having little control over their own learning process while at work. In this study, we aim to discover in what way we can effectively use technology to enhance workplace learning, by synthesizing design propositions for Technology- Enhanced Workplace Learning (TEWL). We conducted design-based research which is cyclic in nature. Based on preliminary research, we constructed initial design propositions and developed a web-based app (software program for mobile devices) providing interventions based on these propositions. In a pilot study, students from different educational domains used this app to support their workplace learning. We evaluated the initial design propositions by carrying out both a theoretical and a practical evaluation. With the insights obtained from these evaluations, we developed a next version of the design propositions and improved the app accordingly. The research result is a set of design propositions for TEWL. For daily practice, the developed web-based app is available for re-use and further research and development."
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Fingermarks have proven to play an important role in criminal investigations for identification purposes. However, in some cases, the donor of the fingermark is not disputed but the activity that led to the deposition of the fingermark is. In this article, the state-of-theart knowledge on evaluating fingermarks at activity level is discussed. First, the relevant variables that should be taken into account when evaluating fingermarks given activity level propositions are reviewed, followed by showing how such an evaluation could be performed using a Bayesian network. Finally, the main concerns and relevant discussions related to this topic are discussed.
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Fingermarks are highly relevant in criminal investigations for individualization purposes. In some cases, the question in court changes from ‘Who is the source of the fingermarks?’ to ‘How did the fingermark end up on the surface?’. In this paper, we explore evaluation of fingermarks given activity level propositions by using Bayesian networks. The variables that provide information on activity level questions for fingermarks are identified and their current state of knowledge with regards to fingermarks is discussed. We identified the variables transfer, persistency, recovery, background fingermarks, location of the fingermarks, direction of the fingermarks, the area of friction ridge skin that left the mark and pressure distortions as variables that may provide information on how a fingermark ended up on a surface. Using three case examples, we show how Bayesian networks can be used for the evaluation of fingermarks given activity level propositions.
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Hbo-studenten doen tijdens hun opleiding werkervaring op, bijvoorbeeld door stage te lopen. Wij onderzoeken op welke manier technologie het leerproces van studenten op de werkplek kan ondersteunen. We ontwikkelen ontwerpprincipes en de daarop gebaseerde Stage-App.Doel Studenten leren op de werkplek heel anders dan op de hogeschool. Het leren gebeurt vaak onbewust en impliciet. De Stage-App helpt studenten bewuster te worden van dit leerproces en hier actiever mee bezig te zijn, om uiteindelijk meer uit hun stage te halen. Resultaten Dit onderzoek loopt. We hebben de resultaten tot nu toe gedeeld via posters, presentaties en artikelen. Gepubliceerde artikelen Exploring Design Principles for Technology-Enhanced Workplace Learning Design Propositions for Technology-Enhanced Workplace Learning Design & Implementation of Technology-Enhanced Workplace Learning Learning Analytics voor Stages en Werkplekleren Workplace Learning Analytics in Higher Engineering Education Automated Feedback for Workplace Learning in Higher Education De open-source Stage-App is beschikbaar via Github.com. Looptijd 01 november 2015 - 31 december 2020 Aanpak In het eerste deel van onderzoek hebben we uitgezocht wat er nodig is om een app voor het leerproces te ontwerpen. Vervolgens hebben we de Stage-App ontwikkeld. Daarin kunnen studenten registreren wat ze hebben geleerd en dit koppelen aan de leerdoelen die ze vanuit hun opleiding meekrijgen. We ontwikkelen de app zoveel mogelijk vanuit het perspectief van de student. Om de app aan te laten sluiten op de wensen en eisen van studenten houden we interviews, enquêtes, gebruikerstesten en co-design-sessies. Tegelijkertijd baseren we de functionaliteiten op literatuuronderzoek over werkplekleren en 'technology enhanced learning', om te zorgen dat de app het leerproces zo goed mogelijk ondersteunt.
